Tech Brew Ride Home - Ride Home AI Fund With Big Technology Podcast

Episode Date: August 5, 2023

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On April 4th, 2023, around 2 in the morning, a man was found stabbed multiple times on a sidewalk in downtown San Francisco. Hey, who did this to you? What happened next turned the story into a political firestorm. Reports have identified the victim as Bob Lee, the founder of Cash App. From Bloomberg Podcasts, this is Foundering, the Killing of Bob Lee, beginning April 16. Welcome to the first bonus episode in a while from the tech meme right home experience. This is Brian and Chris. Chris is here too.

Hi, Chris. Hey, hey, hey. So essentially, we told you or I told you about what we were going to discuss today on the show yesterday. We're going to tee up a podcast episode on Alex Cantrose's pod where we sort of announce the ride home AI Fund. But I also wanted, you know, Chris's, as I said yesterday, 50-50 with me on this new AI fund and Chris's 50-50 on the Right Home Experience episodes, which haven't happened because we've been busy with this fund. So I wanted to give Chris the opportunity to come on and, you know, tell why, from his perspective, he's jumping over to this side of the VC table with me. So, Chris,

This is your therapy session. Oh, my God, yes. Well, you know, I guess I kind of think about the simulation that is the Silicon Valley game. And I've played most of the roles so far. I've been a product manager. I've been on developer platform teams. I've been a founder. I've been a consultant.

I've been a designer. So the last thing, the last boss, I suppose, that I thought I needed to play into. It's funny that you say that. use that term with my wife before, where like VC is sort of the boss level fight where it's like, if I go into this space, then like, there's really nothing else. I mean, I'm sure there will be many other things. It's more a matter of having started my career in open source and being all about building up the web as a platform to now come to a place where I've kind of done enough

tours of duty in different experiences and walks of the founders. journey to recognize and realize that in this moment in particular, it feels that both the allocation of capital to get founders to build into the space and then to provide them with coaching and guidance and advice based on the experience that I've lived in. And of course, that Brian, you and I have talked to so many founders about is going to be necessary to stand out, break out, and succeed in this new space. I would say the other thing that's very important to me is that back in December, I posted chat GPT to Product Hunt and I just happened to find it at the right moment and I got it out there

to the world through Product Hunt, which was the channel that I'm most active on. And it quickly became product of the year. And I knew that this was a big deal, but then having that validation and having so many other people also see it and respond to it in that way, kind of was this signal that so many of the things that we've been talking about in conversational AI and in botland and in Avatar generation was finally going to come together largely due to LMs and generative AI technology. I built a conversational AI company back in 2017. Right.

I don't think people know that you did an AI startup before AI startups were cool. I mean, and it was largely predicated on so many of the ideas and concepts that I'm seeing people build now, but we didn't have LLMs and the compute power wasn't there. And the techniques for building conversational software was more or less rule-based. Someone says this, respond with this, and it was very, very brittle. What we didn't have was building essentially an engine of language and comprehension into the computer that allows us to speak in our natural voice in a way that we're not. that also responds to us in a way that makes sense to us.

And that cuts through a lot of the complexity of computing for so many more people. And so once I saw chat GPT and I saw where this was more or less going, I mean, also was thinking about just the market and how much of a downturn there was and how much, not only like the, you know, we were back into a crypto winter, but, you know, interest rates were rising. All of the layoffs. People forget all of the layoffs that we had to report on the the first couple months of this year. Yeah.

I mean, I don't know what the layoff tracker is now, layoffs. FYI, I think. But it got so high, you know, that it just didn't really make sense to sort of track that as much anymore, but they're still going on. I mean, just today I saw that Discord laid off 4% of their staff.

So there's still continuing to be this retraction. And, you know, as Brian and I, of course, have talked about different ways to collaborate. And it started out with a COVID-era expansion of the TechMeme right home show. So it just seemed that with Brian's background with the ride home rolling funds and my background in Silicon Valley and just our desire to be a part of, I think, shaping this next wave that building a fund would be a way to do that in a way that was different than anything

that we'd done before. And I think we talk about this a bit on the Cantrault's podcast, but I mean, bottom line is, you know, Chris and I are good friends. Chris is a good source of deal flow. There's a lot of times when I'm researching a company and I'm just like, Chris, do you know anyone there? And inevitably, he does. And so, you know, part of this was inspired. There's a very specific investment that the right home original flavor fund made that was based off the Twitter diaspora, you know, all the people that got laid off of Twitter. But essentially that's what Chris and I saw where it's like there were so many great people coming off the bench to do this moment, that that was the real inspiration. But let me give one other piece about this. from my perspective, which was, you know, obviously Chris is a great connector. Obviously, what we both want to do is fund the talent that we see coming off the bench that maybe didn't do Web 3 in crypto, but are doing this now. But also, I'm not a product guy.

I'm more of a business guy than a product guy. So, like, in a way, if there's any startups out there, like, I jumped at the chance to work with Chris because it fills out part of my skill set that I don't have so that if you're an AI startup and you take a check with us, obviously Chris and I are connected. We can help you solve problems, get to the next level, make good hires and stuff like that. But Chris is a product guru, genius guy that can help you figure out how, at the earliest stages, how to make the product good. And so I want to point that out that I jumped at the chance to work with you because I think we, our skill sets complement even when they don't overlap, you know. Absolutely. And, you know, I'll say that one of the reasons why I think it made sense for us to start our own fund, you know, it's possible that either of us, I suppose, could have gone and joined an existing firm. But when I think back to the start of the social web era, which, you know, really kind of got it start in 2005 and six,

And I arrived in San Francisco in 2004. There was a similar kind of climate where there was skepticism and doubt about technology and about funding these things. The dot-com bomb had just gone off and wiped out so many different companies and platforms. And while this time feels different, there are rhymes that are relevant. And the fact that Brian is an internet historian that has cataloged the progression of these things over decades is also a good balance to. my product focus because what we're looking for and what a fund like ours needs to invest in

are products that will take shape over the next five to seven to ten years. And they start with a new set of assumptions that these technologies allow people to build products that have never been possible before. And so therefore, I have to start from a set of original principles that say, this is how the world is going to shape up. This is how the world is going to become. And we want to be part of that. And we see very clearly with some clouds here and there of how we're going to navigate that space and get there.

I'm so glad you said that because I feel like I've been towing the party line where it's like, oh, no one really knows where to invest in the space yet where the value is going to accrue. I think one of the things that you and I both, even before we started talking about doing a fun, like you and I both got right away, no, this is this is a this is a, this is a, this is a, moment where you're talking about the 2004 era where it's like you and I knew intuitively it wasn't over. Don't get out of the game. It's just getting started. I've been towing the party line of like, yeah, we don't really know where do it.

No, I think you and I are like, this is so obvious. And not obvious necessarily in obvious ways, but to us, this is a new era of compute where things that weren't possible will become possible. And it's so like blazingly obvious to you and I. It's not like we have a formula. Well, we can invest in A, B, and C, and we know these are all in. I'll put it this way. I think what you're saying, and it occurs to me.

I wrote this piece a while ago called Seeking Genius in the Negative Space. And the concept was something that I got from Alan Watts. And the idea is essentially that if you're only looking at the positive space, Now, negative space is sort of an artist's concept. So when you draw things, you can draw them based on what you see in space, you know, taking up space, or you can draw the space around an object to remove your biases, to essentially draw what is not there to arrive at what is in the foreground. And so in parts of my career, what I've tried to do is to employ this idea of negative space

to think about, where are people not building anything? because either it's been too hard or it just doesn't make sense or the capabilities, you know, just that aren't there or, importantly, behavior and human behavior isn't at the point where people are wanting these things. You know, when I think back to the hashtag, I could feel intuitively that we needed a way to create kind of like these lightning rods of, you know, social connection through social media. But because so few people use social media and thought it was useful, then, you know, at the time, I was, you know, kind of thought of as probably like a little bit, you know, crazy

because I was solving for something that people didn't yet understand they were going to eventually need. And in a similar way, I see the same thing happening. And, you know, many people do. So it is different this time. But it's not that different from the skepticism and doubt and fear that people have, that there's not going to be any accrual of value into different places. And I think that's what we're looking for. People who have that both belief and also can imagine filling those negative spaces with positive visions

the future through the products and services they deliver. I think I allude to this in the conversation with Alex, but I think one of the problems here is that post, let's call it the app store, the last 15 years, when I say that a lot of investing has been on rails, like if you're starting a SaaS company, you know the levers to pull to figure out how to build it, a DDC company, D2C company. Like, investing wasn't like plug this into the formula easy, but it was kind of close to that. Pretty close. And so people are now looking at a wide open vista.

And they're like, well, where are the rails? And I, and you and I are like, no, where we're going, we don't need no rails. Like, we would, we would prefer a wide open vista than the rails. To us, that's the more exciting investing environment. I think that that's where you and I align instinctively. I think, and to build on that, you know, part of this is that we're participating in those frontier conversations. Yeah.

You know, the, like, it's, it's a funny trope. A lot of people, you know, will make fun of whether San Francisco is back or not. But at the very least, I can tell you that there is so many conversations going on now that we're not going on. Yep. Maybe even a year ago. And if they were, they were just, you know, little piece shoots kind of like, you know, coming out from the surface for the very first time.

And now there's a serious level of momentum in the space to find and discover things to build. And the thing that I'm most concerned about, I shouldn't say concerned about, but that I'm observing, is to your point, Brian, there's sort of a set of known ways to build, deliver, and distribute software products through existing app stores. And I think we have to, again, go back to first principles and ask the question of, well, what should computing be like and feel like if we don't take for granted, something like the app store, existing or something like other types of distribution platforms existing and what types of computing products can be created that reimagine the way in which computing fills up our lives. It's sort of mind-boggling to me to think about all the voice computing devices that now populate our lives and how useless they mostly are and how this era of LLMs is going

to change those products in a way where they actually can become useful because they can back end into services and agents that will do things on our behalf, which is sort of like the whole idea. And so those inputs where we can talk to our computers, I think is going to be a big part of where some of this opportunity is realized. I keep saying that I feel like this is the computing that I always imagined as a kid computing was supposed to be. And there's another investor in this fund whose name y'all would know, but

They have not allowed us to use their name in fundraising. That totally validated this because they said they're from a previous era, and they're like, this is the most excited I've been in terms of the possibilities of new ideas and new companies since my era where I made my name. Right. And I think, again, this is what's been that was totally validating. And I think this is our first principles. So right after this, you're going to hear Chris and I talk to Alex Cantowitz about this. We'll go into more detail about what our specific strategy is and our theory of why this is an investable moment.

But I want to reiterate anyone that is having FOMO about AI. This is a fund you can get in on if you're a accredited investor. We would love to have you. And we're doing the strategy that the Right Home Fund has done successfully for two years, which is we do have some institutional money behind us. We do have larger things and funds and stuff. But we want smart LPs. We want smart money.

So if that's you, right home fund.com. If you know somebody that is having AI FOMO that is smart, send them our way. And again, the formula remains the same as the existing right home fund, which is we can share carry. So if you, first of all, if you're a startup in the AI space, come talk to Chris and I where your buds will be friends and friendly to you. If you know startups in this space, again, get in touch. And if it's a meaningful introduction, we can share Kerry as thanks for these connections. Anyway, Chris and I are super excited. I'll leave you, Chris, with the last word before we seg into the Alex episode.

But right home fun.com, super excited. This is what we've been working on. This is the culmination of actually what Chris and I have been doing on the show for, what, three years now? Yeah, yeah, definitely. Yeah, and I guess, you know, the other thing is that I think ride home experience shows are going to continue to be things that we're going to bring back over time. You know, and I'll probably be starting at my own little podcast adventure as well. We're on that soon. We're on that soon.

Look forward to that. Thanks, everybody. And now you will be teed up with the Ketrowitz episode for more details. Thanks, everybody. Thanks, Chris. Thanks, everybody. Two investors with backing from Mark Andreessen, Chris Dixon, Dennis Crowley, among others, join us right after this to talk about their new fund.

Welcome to Big Technology podcast, a show for Cool Headed, nuance conversation of the tech world and beyond. We have a bonus show for you today. Yes, a bonus show. Two investors, Brian McCullough and Chris Messina here with us today. They're starting a new AI fund, and I thought it would be a perfect opportunity to talk about why you'd start a fund with AI right now. moats? Is there anything investable? And for anyone thinking about what the next generation of

startups are going to look like, well, you're about to hear them. Brian and Chris, welcome to the show. Thanks. Thanks, Alex. So the first question for you guys is, are you bananas? Because I've seen so much discussion on Twitter about people talking about how there are no moats for AI. Very prominent investors, Keith Rabeufoy, Sam Lesson saying that they think that anybody investing in early stage AI right now is relatively insane because the value is ultimately going to go to the big tech companies, Amazon, Apple, Facebook, Google, Microsoft, and the chipmakers like Nvidia. So where exactly are you aiming to play? And why do you actually believe, I mean, you've convinced Mark Andreessen and Chris Dixon and others to join in. So where are you going to play?

Everyone we talk to, no matter what the nature of the call is, eventually it devolves into what are you seeing? And like literally the conversation with Mark Andreessen would, was the same, where he's like, okay, guys, I'm in. Now, what are you saying? Like, it is, it is, but everybody's, it's wide open. I mean, like, literally, if you, if I know that, you know, AI is a thing has been going on forever, but like this moment is, is barely six months old, which actually, Chris and I can speak to that in terms of why we're doing the fund. So, you're calling us investors. We've been on your show before. I'm a podcaster. Chris invented the hashtag, but, um, essentially,

Just investors, but now that you're starting to fund, that's the label you get. So, okay, okay, let me, let me explain as fast as I can. So what we're announcing today is the Right Home AI Fund, which is a $15 million target fund doing seed, pre-seed, Series A in this new AI technology. Most relevant to anyone listening, it's a 506C fund, which is why we can talk about today, which means any accredited investors listening can invest. So if you're having AI FOMO and want to participate, in this moment, but you can't get into an A16Z fund or a Thrive Fund. You can get into our fund. So

check out ridehomefund.com for more info. But essentially, it was almost inspired by Chris. I've been running the ride home fund for two years, and Chris was always a great source of deal flow. And my remit to him was always like, if there's somebody coming off the bench that had a previous exit or that you've known for a while that by definition you'd invest in whatever, they were doing next, send them my way, and around December of last year, it all became AI stuff. And these were folks for whom this wasn't their first rodeo, who didn't bite on Web 3 or crypto or whatever, but were activated by this AI moment. And we can give you examples if you're interested. But that also activated Chris, which he can speak to, which is we were both

like, we want to back these people. The talent of our, you know, we've both been in the Valley for over 20 years, the talent that we're seeing coming off the bench activated by this moment, we just wanted a fund to back those folks. Okay. The real question is, where's the investment opportunity? I mean, that's, so of course, you're on the phone with Mark and Andreessen and he's like, yeah, of course, there's opportunity there. But again, what everybody's saying about AI investment is you have the big companies

and they're going to crowd out any seed company that you're funding that doesn't have, For instance, like the money to spend on the GPUs or potentially they're building a thin layer on top of something like a chat GPT and chat GPT could just subsume it. For instance, character AI, right, which is like it allows you to chat with all these historical figures. Like, it's very easy just to go into chat GPT and be like, all right, chat GPT or Bing or Bard. You're a blink and let's have a conversation and it will do that. So then what's the value of character? So where are you guys seeing specifically outside of the people? the investment opportunity to actually make a splash here with seed companies and series A companies

that some of these other luminaries like a key through boy or a same lesson are saying do not exist. I think the skepticism or the reluctance from a lot of folks is exactly the moment to lean into this because now is when we're going to be learning what types of products actually make sense. So what Brian and I ultimately are looking to invest in is the productization of these new techniques. that start from an assumption that software and technology and that the way that humans actually use computers is going to go through a rapid revolution, but that those existing incumbents are going to defend their existing models and how they make money currently, whereas a bunch of other folks who don't have to worry about that can build something entirely new that are set

with new assumptions. And so part of that is looking at behavior. That's a big piece of how we learn to build social software that people actually wanted to use. And then the second part is coming up with generational brands that actually reconstitute existing marketplaces or product experiences that were in the marketplace, but that can be remade through technology. So looking back on things like Airbnb and Uber, suggest that these were ideas that people understand. You know, you have property, you want to rent it out. You have a vehicle.

You want to lease it out or you want to drive people around and charge people for that. But bringing technology like GPS and mobile phones to that allowed for these large companies to be created. And I think in a similar way, we're going to see the same thing with AI and G.I. generative AI. So I'm being reminded now, like hearing the way that you guys speak of this stuff, I'm being reminded of a Benedict Evans tweet where he talked about, the answer is not that you're going to start to talk to Microsoft Excel. It's that the way that you do spreadsheets just changes because into a completely different form factor where you're going to upload, for instance, the data.

Exactly. Why do you need a spreadsheet? You'll just upload the data and talk to it. I would use the analogy of like, if this is a paradigm shift in compute, which we believe it is, what was the thing in the paradigm shift of the PC era that sold PCs was the spreadsheet, something that didn't exist before that paradigm shift that allowed accounting to 10, 100x or whatever? We're obviously looking for those things. But let me back up for a second. Fundamentally, what we believe is, like, you ask the question, like, well, will the incumbents or the people with the largest models always win? If that ends up being true, then yes, this is academic. But we don't believe fundamentally that's true. We believe that fundamentally,

this is still software. Like, how did Zoom win over other sort of, you know, conferencing software? Why does this one win over that one, Figma win over that? Like, in the end, it's the end result of what you do with the software for users in terms of their productivity and their delight in the product. For all of the talk about generative stuff and AI stuff, in the end, it's software and in the end, it's inputs and outputs, right? So we have this theory that while everyone is still looking for what the, you know, investing in this is not on Rails yet in the same way that has been for things like SaaS or like D to C companies that people understand.

This is how you build a company that reaches this many users or customers or something. But in the end, we think that on the input side, it matters. and Chris will go into this about our theory of AI varietals, but it matters the models. It matters the data, the input that creates the things, and it matters the output. So you could have three different startups that are like, we use AI to look at x-rays and find cancer, right? But what have you trained that on? And does one model work better than the other?

And already people are talking about things like accuracy and not having hallucinations and stuff like that. So people that get more accurate will win. But also, what have you trained it on? Is it, do you like the results it gives you? Does the output, well, this output is more accurate, but that output, like, in a clinical setting, allows me to interact better with my patients and things like that. So in the end, we believe that this productization is the way to go, because it will be the inputs and the outputs with the underlying software and AI stuff sort of abstracted a way that will matter. And the analogy that I have to give Chris credit for for coming up with is our theory of

varietals like wine. Hold on. We're going to get to your theory, but I also want to ask, isn't this kind of a tough area to invest in because, you know, what is in an AI company? Like if I'm investing in social media or I'm investing in CES, okay, I know what I'm doing. If I'm investing in AI companies, all of a sudden, you're the range of companies, like you guys can be consumer, you can be business, you can be anything. So how do you pick what you invest in?

And then we can get into your varietal theory. It's back to people. It's back to application of the productization. Can I give you an example of a company that we actually have cut a check for? Wait, you guys have already cut a check and you haven't even finished raising your fund? It's a 506C. We're allowed to do that. We're moving fast.

That's the whole idea. Yeah, let's hear it. Yeah, definitely. AI, fix-it-yourself.a.ai, is training models on all of the world's sort of owner's manuals, users manuals, specifications and things like that. The idea being, train an AI bot to fix your dishwasher, repair your car, my printer all of a sudden isn't working or is flashing this green light. What does it mean? As opposed to going in and finding the PDFs or calling the 1-800 number, they're training on every product under the sun. They're refining the model in terms of,

can this be a white label thing that a Samsung or a frigid air or whatever would use to sort of be the sort of bot that would interface with the customer so that the customer doesn't have to call the 1-800 number. So it would save on things like, you know, warranty stuff or whatever. Or also, on the consumer-facing side, what if there was one bot that any time, something broke, you could use your smartphone to like turn on the camera and be like, okay, the dishwasher isn't working. Look in the back there. Oh, that hose is disconnected and the bot tells you, well, what that means and X, Y. So this is inputs and outputs. We love the founding team. They have previous experience in the space, relationships with, you know,

OEMs and things like that. Like, that is sort of a definitional example of like sort of the productization that we like. It's not, The only stuff we'll invest in, but like that's where we're seeing stuff that we get excited about. Yeah, I like that. I mean, the idea that I could like, for instance, you know, converse with my refrigerator to try to figure out, like, how it's broken. Yeah, that would be great. The analogy I use is, like, you know how every website has like the sort of chatbot on the bottom right-hand corner that if you have a question, like the AI? Well, imagine a chatbot AI that comes into the real world into meat space, not just on a website, right?

Yeah. I think Elon's working on some of those. We just had Ethan Mollick on the show. He's a professor at Warren who assigned his students to use chat GPT in class and talked about how everyone's going to, you know, lots of students are going to be cheating with this stuff. And I personally cannot wait for the first person to cheat with chat or chat refrigerator. And, you know, like, you know, the paper include the term. As an AI refrigerator, I cannot complete your paper.

However. So let's hear about this AI varietal's theory. So what does that mean? So to, I think it generalized from the example that Brian just gave, when we were going through this exact exercise, when we were trying to decide, you know, do we want to do this fund or not? And why now? And why us?

It stood out to me that there's been this reframe, or reframe, rather, in the business that data is the new oil. And it's been bandied around for quite a while. And the assumption is that if you have just a load of data, you know, you've got some data lake or warehouse someplace on the internet or in someone's cloud that you have an advantage for both training and building AI products. And while there may be some truth to that and having an enormous amount of data can be useful, there's also a lot of crap out there. There's a lot of stuff that's undifferentiated that's just kind of nonsense. And, you know, having worked at various tech companies, I know for a fact that. a lot of the stuff inside of these spreadsheets or whatever just is not structured in a way that

can be useful for training these datasets. So as I was thinking about a better way to think about the opportunity, it occurred to me that it's not that data is the new oil. It's that data can be thought of as a type of terroir. And obviously coming from California, being in California now, we've got Napa Valley right up to the north. And so there are all these places throughout California, where the terroir, the earth, the place in which grapes grow, represent different types of cultivation opportunities. So essentially, by cultivating the land and growing grapes in it, and then harvesting those grapes, which, of course, have grown in different climates with different soil types. That produces different types of expressions in wine. And those different expressions in

wine, if you bear with me for this metaphor, are kind of like the types of products that we expect to be able to create from creators of these products that understand deeply the data that they're working with. Maybe they've actually set up the data ingestion pipelines and the refinement pipelines. They understand deeply a customer segment and the needs of those customers. And perhaps most importantly, they have the vernacular or the language of that customer and they know how to speak that customer and to deliver products and services that fit into the environment or the industry that their customers are in. So it's not enough to just have a whole shit ton of data

and just to build a company or product. You actually have to have some empathy for the market that you're dealing with. And we think that that's going to be the opportunity for founders that are thinking about that and are thinking about the whole lifecycle of building AI-powered, AI-enriched products that there are going to be opportunities.

And these opportunities are going to take many, many years to play out, Well, many years, like in my thinking, it's like, you know, three to five years, maybe eight years. But nonetheless, now is the time to start. Now is the time to learn. Now is the time to experiment. And for those founders who either have left big tech companies or, more importantly, were laid off or fired from those companies, they're going to be hungry to be building those products and those services. So that's really where I think Brian and I, you know, both students of history, both internet history as well as social media history, as well as social media history,

longer term history, are seeing opportunities for us to support those founders, coach them through launch, and help them get distribution and to be discovered. I also think, Alex, that it is going to be, there's going to be a ton of M&A over the next three years, right? So I, like you, have seen, like the studies and things like that, and anecdotally, oh, we didn't expect that all of the incumbents would adopt this AI stuff that quickly, right? Like everybody and their mother has added AI features to their existing products, right? Where it gets tricky is where it gets fundamentally disruptive to, like, again, Microsoft adds AI to Excel, but what if you had something that AI could do that obviates the need for a spreadsheet entirely, right?

the thing that we're looking at is like again to use the spreadsheet example like Chris and I believe me there are a hundred different startups out there that are like draw on a napkin a room and the AI will generate like sort of the the perfect interior design beautiful interior for you yeah but like my wife is is an architect and every time those come through we float them by her and she's like, can it create a BIM file for me that I can send to the structural engineer? No. Why? Because it's two kids, 25 years old from Stanford. There's no architects on the thing. You know, she's like, you know, that we have, I'll lose my license if things do not meet certain, like, building code standards and things like that. So, like, our, like, our dream sort of

company to come our way right now would be, like, a 25-year-old from Stanford. That's AI guru. an architect with 20 years experience that understands, you know, the needs of the profession and the, and someone that's ex-autodesk, right? Because what my wife is like, is like, the day that you could come to me and you could train my, you could train an AI on my previous, you know, career-long history of drawings and like, this is how I like to design an interior. This is how I like to. And you could do the napkin sketch into the AI thing, but it's based on what I like to do, so it's like my style of design and it's functional so that in a day I could have BIM files that are actionable, that's the 10x sort of equivalent to the spreadsheet.

Yeah, I think maybe, Brian, another way to layer this is I do like Microsoft's frame of co-pilots. And if we think about these as tools for collaboration and for reasoning and for thinking through or going through the creative process, then ultimately you kind of want to mix where you know, as Brian said, like Lisa would submit her designs to train an AI. She would produce a series of sketches. She would then submit them to the AI to get some other ideas or other directions, perhaps returning sketches in her style in order for her to work out the thought process. And then when it's time to actually move forward into the finalization workflow,

then she could go into a mode that is all about that type of collaboration. The problem is that so many of these generative AI tools, tools are designed only on the final product and the outcome. And those outputs and outcomes are based on a popularity contest on the internet, which is all good and well, but not necessarily the most appropriate for coming up with novel ideas or synthesizing new outcomes or coming up with entirely new concepts or practices. So it's great for maybe returning to things that have been done or are well understood in the marketplace and are therefore somewhat commoditized, but creating things that are new expressions and creative, I think still is an area where there's

loads of opportunity. Yeah, this is interesting for two reasons. The first is that it seems to be an application that something like a Google will not want to go after because it's just small enough to be under the radar for them, but just big enough that could be a really interesting company. And the second reason is that because we talk about generative AI and it seems like the conversation always goes toward chatbots. But if it can go towards, for instance, blueprints or how.

having a dialogue with other like important technical but creative images, then you could really, and plans, then you could really get into an interesting place. We're here with Brian McCullough and Chris Messina. We're running this both on the big technology podcast feed and on the Tech meme right home feed. If you're a big technology podcast listener, I definitely think that their show is worth checking out. Brian's show is worth checking out every day, a little update on what's going on on tech. And if you're a Tech meme right home listener, I'd say, you know, come give Big Technology

podcast a shot. We do weekly, twice weekly interviews. Oh, sorry. I was going to say how many times have we seen on Twitter? People say that they use a tech meme every day and your show for the in-depth sort of stuff twice a week. I think it's a great pairing. It's been, it's really, it does.

If you're going to think about your tech podcast media diet, you know, I think putting those two together, that's the way to go. All right, let's take a quick break. We'll be back on the other side of this break to talk about how these two were able to get in front of the Mark Andrescans and Dennis Carly's of the world, and we're able to convince them to invest. And then we have a couple of AI-related stories that we want to talk about, AI warfare, AI, and the Hollywood Strike. We'll make it a quick second half. So stick with us. We'll be back right after this. And we're back here with Brian McCullough and Chris Messina,

two investors who are raising a $15 million target fund from investors, including Mark Andresen and Dennis Crowley, Chris Dixon. I have some thoughts about Mark and Dresen that maybe I'll share in a different show. But in the meantime, I'd like to hear how you were able to get in front of him to raise the money from him. And don't you, doesn't he also have like an AI related fund? So talk a little bit about that process. Yeah, sure. The short answer is that it's because Mark and Chris Dixon listen to the show. Chris is very kind. He has said multiple times that when the Andreessen

Crypto Fund invests in a company or hires new people, they give them my book. So the bottom line is, is that actually, it was Chris and Mark, those were the first two LPs we reached out to. There were some other luminary names that you would know, but have not agreed to allow us to use their names to fundraise.

Essentially, we went out and we said sort of what you said at the beginning, which is no one knows what the space is. Come in with us and, you know, as an LP, you'll be able to see the people we're seeing and the companies and ideas that we're seeing. Great. So we have a few minutes left together. I thought that, you know, we're doing this as a special episode, but we still want to cover some of the news. I feel like doing a big technology podcast or a tech room right home show without going over some headlines would be a complete waste. So let's not waste this opportunity. Now, we're in the middle of this big, writer and actor strike inside Hollywood. And we put a document together to talk about, you know,

to sort of discuss the type of stories we wanted to cover. And, you know, usually I like to go through like a more robust setup talking about the story and what's happening and then ask a pointed question. But there's a one liner in this document that just said, AI and the Hollywood strike, Brian's anecdote without any detail. And I was like, I'll be damned if I don't ask about that. So, Brian, let's hear, let's hear your perspective on what's going on here. seems like you've had an interesting interaction. So I, you know, I do daily tech news and do headlines like you do headlines on your show. So you might have done a similar piece.

I think it was in the Washington Post maybe where they were talking about how in this sort of strike moment where how long is it going on more than two months now? Like this might be the moment where TikTok stars become the writers, the writers and the now the actor's strike. Yeah, that's shorter. Oh, yeah, go ahead. But that studios might gravitate towards TikTok stars since they're not in a union to, in the same way that in the strike in the in the in the in the, in the odds that sort of begat the the takeover of reality TV because it was cheaper and non-union. And so TikTok stars might be moving over to to fill the gaps of what Hollywood needs for content. At the same time, the article posited that this was training folks that were. in Hollywood, there were actors, writers, writers, or whatever, to be like, I need my own platform,

almost push them into the creator side of the equation. And so the article was positing that this could kill both sides of the equation in terms of like the traditional Hollywood model. And so my anecdote is this. You know, I'm in podcasting. I talk to a lot of podcasters. I also, weirdly enough, have a background in comedy and stand-up comedy and improv and stuff like that. a lot of the shows and friends that I listen to their podcasts are like comedy podcasts, but like, let's just say a broader picture, people that work in Hollywood, right? All of these years, they've had podcasts like comedy and various Hollywood folks were early adopters to podcasting because it was like a supplemental thing.

Like, if you can get staffed on a writer's room for a couple years, then you make a decent living, but then you might not be staffed on a writer's room for a couple of years, or like actors know you go from roll to roll or whatever. And comedians, you know, you go touring, but then, you know, the pandemic cut down on touring. So here's my anecdote. The people that I know that run comedy podcasts and have done for, it's not like they just started it because of the strike, they've been doing it for five or six years. Almost to a person or to a podcast, they have suddenly gotten extremely serious about it where people have, launched memberfuls or patrons or whatever, where, now, you could argue that people are doing this

because they're not getting income. But what I've been seeing over the last two months, and this was really hit home to me last week, where I realized that every comedy podcast I listened to has sort of gotten more professional about it, doubling their episodes and things like that. I'm seeing the people that I know in comedy, they used to think of doing these side hustles, a YouTube page, a Twitch page, a podcast or whatever, as like, this is what pays the rent in between my main gigs. I think they're literally getting sort of evangelism about, like, well, this is my main gig. And if I get a show, then, like, that's just gravy. So you're saying that the creator economy was delayed by, like, three years. And now,

thanks to the strike. Or the creator economy had been to this point, the people that were non-professionals that we're trying to break in. And I'm seeing it from the reverse now where the professionals are like, screw the Hollywood system. I can probably make more money and have, even if it's not more money yet. Do you think it's really screw the Hollywood system, though?

Because it seems like there's this desire to get paid the way that Hollywood pays and that the critter economy is, you know, as you both know, like a slog. It's a lot of work, you know, especially if you're doing, you know, your own stunts effectively. So is there actually a desire

to dispense with the Hollywood system? which, as I understand, you know, relatively pays well, especially through, like, union fees. It might actually, yeah, it might actually be a reverse of the way that we've seen it play out in journalism, where in journalism, the stars have actually, like, gone and done their own thing. Substacks and stuff. Yeah, substack, because they know they can make more money. It's more stable. The business sucks.

And so they've actually gravitated towards this, like, I will insulate myself from the pressures of the business. See, news, like, yeah. But that's what I'm saying here. Yeah. It's different. Hollywood. That's what I'm saying it's going to be the reverse. In Hollywood, you might have a place where the stars, this system is going to really work very well for them.

Barbie movie, Oppenheimer movie. If you're a star in one of those movies, you're not, you don't care about having your own podcast. However, this is something that the middle class and even the bottom of, you know, actors and comedians, they're extremely entertaining. They're very talented. They can be engaging on their own. and this strike might be a wake-up call for them where they say, hey, now I'm going to take advantage of this system so it will be flipped, where the middle class will say, I can make money and protect myself, and the stars will stay with the system, whereas in journalism the stars have left, and the middle class has remained with the system. Let me give you a middle class example, and I don't know if this will, people, everyone will agree with me, this is middle class. But you know the Office Ladies podcast, which is Jenna Fisher and Angela Kinsey from the original.

show, the U.S. show, The Office, Pam and whatever the other. So, now, those are examples of actors for whom I'm sure they've gotten residuals from, for whatever degree the office did play on cable television. But once it's gone to streaming, residuals and things like that, stop. The Office Ladies podcast, I guarantee you those two ladies are making seven figures a year from that podcast. And so, imagine. the equivalent of Jenna Fisher today from an equivalent show where sure you get paid well for the two seasons that Netflix gives you before they cancel the show. But you have this fame and you have this level of notoriety. Don't you have to have the fame? Like that's not middle class. I'm sorry.

That's like, I could give you other examples of people that are like- middle class of Hollywood. That's different than the middle class of America. I see. That's not Tom Cruise. Right. I try to caveat by saying, you would. wouldn't agree. But so imagine a player actor on an equivalent television show today that was a big hit on Netflix that runs for two years that has no residuals. So you got paid well for two years, but you don't get to do anything else with that, right? You could be the equivalent of Jenna Fisher and be making millions of dollars a year by parlaying that sort of fame into a podcast or a YouTube channel or whatever, a platform that you own and you can

control and you can still get a show or get a movie, you know? You know, so to add to this. That's it. What? I'm surprised at how sort of negative you are to this idea. I feel like that this is like training people to grab the means of production in a way that they were only dabbling in before. I guess what I'm suggesting that is that you're still dependent upon these streaming platforms and the algorithms that sort and organize the content. Now, that is not absolutely true if you do, well, I was going to say a substack, you know, sort of tries to have this, you know, perception of being neutral.

But now that they have notes, they are getting into the business of algorithmic amplification or at least choosing what, you know, rises at the top, as opposed to an email inbox, which currently at least so far is still reverse chronological. So my point is that especially for media talent, they are dependent upon platforms like YouTube or Netflix or. or TikTok or reels and those types of rich media platforms. And so that's why suggesting that the workers can seize the means of, you know, production and distribution, I think is, is not quite accurate because it's just substituting the previous gatekeepers with a new set of algorithmic gatekeepers. Okay, let's let's move on to, um, actually,

I want to say one more thing. Because I think it is, okay, it is relevant to this. I was listening to the artificiality podcast this morning. And Jonathan Colton, who's a musician, um, made a very useful, I think, point. which is to say that the ability to make and derive an income from entertainment is a relatively novel thing in human history. And the fact that we've created a regime, intellectual property controls, to protect ideas, is something that has only come around in recent human history. It's not something that is guaranteed. It's not something that we necessarily have to persist forever.

And especially in the era of generative AI, we may have to rethink the way in which intellectual property and that type of production actually functions. So I thought that was actually very useful. I think that person is so completely wrong. And entertainment is definitely going to be here to stay. But we'll record. Let's record. We're going to do another one of these.

So let's table that. We'll come back to it. We'll see how it goes. There's this wired story that's completely wild. It's called the AI power, totally autonomous future of war is here. I mean, there are some quotes in there that literally come out of a movie. So there's this Israeli guy, Amir alone, who's built, who's part of this company that's built this autonomous speedboat called the Siegel.

And he says that it can be equipped with a remotely operated machine gun and torpedoes that launch from the deck. And he says, it can engage autonomously, but we don't recommend it with a smile. We don't want to start World War III. And the article, the next paragraph, goes on to basically underscore what this means. Autonomous systems with the capacity to kill already exist around the globe. In any major conflict, even one well short of World War III, each side will soon face the temptation, not only to arm these systems, but in some situations to remove human oversight, freeing the machines to fight at machine speed. In this war of AI against AI, only humans will die. And it's so interesting to me because obviously we do have this advanced, you know,

AI technology that can kill people. But I look at that and I look at like the biggest war in the world right now, which is the Ukraine war, and you have Russians and Ukrainians, like, fighting side by side and sort of World War I style trench warfare. So, you know, my question is, like, you know, it seems clearly that this idea of AI warfare is overhyped, and maybe we have just reached a state of, like, we've armed ourselves to the gills, you know, with technologically advanced weapons. And it does seem like there's just so much reticence to use them that, I mean, we do, I guess we have Ukraine flying drones into buildings in Russia as we speak, but it just, the juxtaposition of that is so interesting. We have trench warfare. That's really what's happening. And all this AI technology in

the world, like, it's like the most thing that, the thing that's being used most is Starlink, where the Ukrainians can communicate with each other. What do you guys make of that? It seems like a contradiction. AI investors. Where is the contradiction? Okay, your, your point is that trench warfare is warfare that is being waged in 2023 while we have the technology to essentially execute autonomous warfare. So it seems like there are a number of factors to that. One being that, you know, that type of, I mean, those technologies are being deployed increasingly, for sure. And we know that the drone technology has improved greatly and that Ukrainians are finding new ways to improvise and create new types of explosive devices that drones previously were not meant to be,

as far as I know, sort of used or created for out of off-the-shelf components. So that is happening. I think the question then is, to the degree that you have, what does it mean to have a number of robots and self-directed machinery more or less mowing down humans if one side doesn't have to actually deploy humans onto the battlefields? at all. And what does that mean, morally, to essentially annihilate? I mean, it's a type of, I don't know what to call it. It's not, it's like robicide. It's not genocide. But essentially, if you have the ability to do that, you can just decimate people. That is definitely genocide. If you're using robots to kill people, like you are, you can't take the human out of that. It's

robot assisted genocide, maybe, but it's genocide. Sure. But I guess I'm asking the question, like, what are you sort of, it feels like the way in which the quote unquote rules of war have been developed is such that there is a sort of desire for two different sides, depending on the type of war it is, but in this case, it's a territorial war for those who desire to maintain ownership and possession of land or a specific place to fight for that land. And at some point, the ability for one side to, you know, declare that they're done fighting and they throw up, you know, the white flag and they surrender, you know, sort of there's a, perhaps an honor in that in terms of human society and civilization.

To surrender to robots that have, you know, executed warfare against you feels like there is something completely lost in at least the traditions of war and that we're not quite ready for societally, like what that would mean. I guess what I'm trying to say is like, where is this weaponry? I mean, is it actually being used in the conflict? The fact that, like, it's being built up this way. Let me, let me build off.

Be there. Let me, let me build up off of something that Chris said, tangentially, which is like, so in the history of warfare technology, what always happens is somebody, there's a technological leap

that one side has, and they completely run the table on the other side. So you can talk about the machine gun in the Borough War, but yet in World War I, people hadn't learned the lessons and they were still rolling out cavalry, right? In World War II, you know, basically battleships

were obsolete because of the aircraft carrier, but you still had, you know, the battle... Also some rains. Right now, today, people are questioning to the degree that any surface Navy might be an obsolete technology because of the nature of missile technology, etc. So Chris is saying we have the ability right now for any combatant to have a drone swarm that is not controlled by human pilots or whatever, and then goes after troops on the ground or, God forbid, civilians and cities, etc., etc.

Okay, that will happen, and that has happened, by the way, and there's wars going on in the Caucasus right now where that is going on. The reason it will happen is because it's sort of Moore's law for weaponry, which is, you know, like in the stupid latest Top Gun movie with Tom Cruise, they don't need pilots anymore. Well, you don't need... It's sort of romantic. But you don't need...

You don't even need to train people to sit behind a laptop and guide the drones anymore, you can send out a swarm of drones and be like, just decimate everything in this valley, right? I know this sounds terrible, and I agree morally it's terrible. It will happen from one side to the other because it'll be so cheap for them to do that it's the Moore's Law of the destructive power of the technology. So what Chris said was that will happen. It will be a bloodbath, and then people, the other side will learn, well, then we need our own drone swan. that can combat the drone swarms. And so I'm not saying that we're anywhere close to, like,

what was that movie where it was like you had giant mech robots that fought over Alaska or something? Avatar, too. Isn't that like almost all movies? Yeah. I don't know. This is not going, I guess it just doesn't seem like this is going in a good direction. This is scary stuff. Are you guys going to invest in military AI technology?

We have no plans to. Absolutely not. Plans too. We want to 10x what people do. productively. We want to invest in products, not in weapons. Brian and Chris, thank you so much for joining. Just a true pleasure to speak with you guys. Let's do this again sometime soon. Congrats on the announcement. The first show, I think, that you're talking about it, is this one. And we always love breaking news here on Big Technology

podcast, so thanks for helping us do it. Congratulations, and we'll speak to you guys soon. Thanks, Alex. Thanks so much. And thanks to all of you, the listeners. We'll see you next time on Big Technology Podcast.